Despite its high share in national energy demand, the tertiary sector is an undifferentiated residual in the energy balances of most countries. To develop effective policy measures for enhancing energy efficiency, policymakers need a sound understanding of how the energy demand is structured. To date, only a few studies assess energy demand in the tertiary sector quantitatively. This paper aims to close this gap by introducing an integrated model that transparently breaks down the energy demand according to statistical subsectors, energy carriers and end-uses. The model combines a technology-based bottom-up with a top-down approach and applies it to a case study on Germany based on survey data from companies. Model validity is analyzed using a set of indicators. The results for Germany show that the model is consistent with the national energy balance showing an aggregate deviation of only 1%. The results for 2019 indicate that electricity demand in Germany’s tertiary sector is dominated by lighting (35%), information and communication technologies (33%) and the provision of mechanical energy (9%), while fuel demand is mainly due to space heating (78%), followed by mechanical energy (15%).

Energy system models or energy demand analysis, such as top-down and bottom-up models, provide energy consumption data in energy end-uses, energy carriers, and subsectors. A technical energy efficiency potential can be determined by applying the best available technology (BAT) values. This paper aims to take the consideration of the energy efficiency potential in an energy system model to a new level by including environmental and social aspects. Using the example of the tertiary sector, it is shown how to incorporate a quantification methodology for non-energy benefits (NEBs) together with the (avoided) environmental costs into the energy efficiency potential of an energy demand analysis. This leads to an overall environmental assessment of the tertiary sector and shows how integrating avoided environmental costs and NEBs increases the economic efficiency, cost-effectiveness, and profitability of energy efficiency measures. Assuming a price of 29.04 EUR-ct₂₀₂₀/kWh for the (avoided) environmental costs and a ratio of the total net savings to the net energy savings of 2.3 for the NEBs, all considered energy efficiency measures are economic. This paper shows that including environmental costs and considering NEBs could be important policy instruments.